The prevalence of mental distress is higher among university students,
and mental health disturbances are expected to rise amid significant
social crises such as war. First-year students who enrolled in
university programs after higher education institutions reopened in the
midst of ongoing armed conflict face greater mental distress as they
adjust to university life and deal with the aftermath of war. Therefore,
this study aimed to investigate the prevalence of depression, anxiety,
and stress and the predictive roles of social support and dysfunctional
attitudes to determine the level of mental distress among students. A
cross-sectional survey study was conducted among 335 first-year students
at the University of Gondar. A multistage sampling technique was used to
enroll participants. Data were collected using the depression, anxiety,
and stress scale (DASS-21), the short version of the dysfunctional
attitude scale, and the multidimensional scale for perceived social
support (MSPSS). To determine the prevalence, descriptive analysis was
used, followed by a t-test to compare gender differences and multiple
regression analysis to examine associated factors. The sample comprised
56.4% of male respondents, and the mean age was 19.93. (SD: 1.28).
Depression, anxiety, and stress were prevalent among 72.8%, 69.3%, and
57.3% of the participants, respectively. While sleep and appetite
problems were strongly associated with depression, anxiety, and stress,
previous mental disorder diagnoses and fear of poor grades only
significantly correlated with depression and anxiety. Excessive internet
use, on the other hand, was correlated with increased anxiety levels.
Multiple regression analysis revealed that social support and
dysfunctional attitudes explained 21% of the difference in students’
levels of depression, anxiety, and stress. Social support was the
strongest predictor across all diagnoses. In conclusion, a high
prevalence of depression, anxiety, and stress was reported among
students, and the level of social support received was found to be the
strongest predictor. Therefore, interventions aimed at expanding
students’ social networks and access to social support are recommended.